Patient medical specimens are commonly analyzed in high volume automated analyzers. Such analyzers, which are often capable of performing a number of tests, are produced by companies such as Kodak (the relevant division of which has been purchased by Johnson & Johnson), Miles Laboratories, Ciba Corning, Abbott Laboratories, Coulter, Medical Laboratory Analysis, and others. Many of these analyzers are quite complex; for example the Kodak E750-XRC analyzer is able to perform twenty-two tests on a single patient specimen, the tests being selectable by software input.
It is common practice in the use of such analyzers, and indeed mandated by government agencies in many countries (e.g. the HCFA in the U.S.) to check the quality of the results produced by the analyzers by periodically inserting control materials for analysis. The control materials, which are non-patient specimens prepared by commercial suppliers (frequently by the manufacturer of the analyzer in question) are analyzed by the instrument. If the results of the control material analysis vary from the required levels by more than a selected amount (the various tests used will be discussed), then the analyzer is considered to be functioning improperly.
Although the above-described method of quality control has been used in virtually all developed countries for many years, it has serious disadvantages. One disadvantage is that if as a result of analysis of a control material it is found that the analyzer is functioning improperly, then all of the patient specimens analyzed since the previous quality control check (at which time the analyzer was functioning properly) must, depending on the nature of the malfunction, be reconfirmed (and often re-analyzed). This is a costly and time consuming process.
A further disadvantage is that at the present time, there is no logical method for determining the length of an analytical run between insertion of control materials. In some cases there are government requirements, e.g. CLIA in the U.S. requires for many analyzers that control materials be inserted once every twenty-four hours. In practice laboratories may do so more frequently, e.g. once per shift (for example once every eight hours), to reduce the loss should it be found as a result of such an insertion that an analyzer is not functioning properly. However the same problem, namely the requirement to re-analyze patient specimens, still exists. In the extreme, to have complete confidence in the results it would be necessary to insert control materials after each analysis of a patient specimen, but this would obviously be impractical since it would be far too costly and time consuming.
An alternative procedure, referred to as the "Average of Normals" method of quality control, was described in an article by R. G. Hoffmann et al. entitled "The Average of Normals Method of Quality Control", American Journal of Clinical Pathology 1965; 43: 134-141, and has been described in more detail in an article by George Cembrowski, E. P. Chandler, and James O. Westgard entitled "Assessment of "Average of Normals" Quality Control Procedures and Guidelines for Implementation", American Journal of Clinical Pathology, Vol. 81, No. 4, April 1984. In the Average of Normals method, an error condition is signalled in an analytic process whenever the average of selected consecutive patient data is beyond the control limits established for the average of the patient population. When an error condition is signalled, the procedure is the same as that employed when a control material is inserted and an error is found in the analyzer response, namely the preceding run of analyses is rejected and the analyzer is inspected, recalibrated and if necessary repaired. The rejected analyses must then be re-performed before they can be reported to the laboratory's customers (usually physicians). The Average of Normals procedure has not been widely used since it requires detailed simulation studies for each analyte and method; it generally requires computer support to implement; it is not readily applicable when patient populations are unstable, and it is too difficult to make judgements from it as to whether a run should be rejected or reported.